Code optimization for code compression

Drinic, M.; Kirovski, D.; Vo, H.

doi:10.1109/cgo.2003.1191555

Cited by 5 publications

(6 citation statements)

References 17 publications

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“…Drinie et al [2003] present two preprocessing steps for code compression that explore the syntax and semantics to improve the compression ratio. They employ a heuristic to partition the program binary into streams with high correlation.…”

Section: Pattern-based Code Compression For Memory-constrained Systemsmentioning

confidence: 99%

Access pattern-based code compression for memory-constrained systems

Öztürk

Kandemir

Chen

2008

ACM Trans. Des. Autom. Electron. Syst.

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As compared to a large spectrum of performance optimizations, relatively less effort has been dedicated to optimize other aspects of embedded applications such as memory space requirements, power, real-time predictability, and reliability. In particular, many modern embedded systems operate under tight memory space constraints. One way of addressing this constraint is to compress executable code and data as much as possible. While researchers on code compression have studied efficient hardware and software based code compression strategies, many of these techniques do not take application behavior into account; that is, the same compression/decompression strategy is used irrespective of the application being optimized. This article presents an application-sensitive code compression strategy based on control flow graph (CFG) representation of the embedded program. The idea is to start with a memory image wherein all basic blocks of the application are compressed, and decompress only the blocks that are predicted to be needed in the near future. When the current access to a basic block is over, our approach also decides the point at which the block could be compressed. We propose and evaluate several compression and decompression strategies that try to reduce memory requirements without excessively increasing the original instruction cycle counts. Some of our strategies make use of profile data, whereas others are fully automatic. Our experimental evaluation using seven applications from the MediaBench suite and three large embedded applications reveals that the proposed code compression strategy is very successful in practice. Our results also indicate that working at a basic block granularity, as opposed to a procedure granularity, is important for maximizing memory space savings. © 2008 ACM

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Section: Pattern-based Code Compression For Memory-constrained Systemsmentioning

confidence: 99%

Access pattern-based code compression for memory-constrained systems

Öztürk

Kandemir

Chen

2008

ACM Trans. Des. Autom. Electron. Syst.

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“…Despite this inconsistency, current codes do not provide much guidance on the required deformation capacity of the diaphragm. Codes do include structural integrity requirements for diaphragms compatible displacement demands (ACI 318 2008) (IBC 2003), however with little guidance on how to meet these requirements. As a result, most designers consider diaphragms to be elastic force-based elements and considerations of deformation capacity are not part of the design.…”

Section: Intent Of Code Provisionsmentioning

confidence: 99%

“…The PDH structure seismic design is based on existing code (IBC 2003), with the adoption of certain aspects of the emerging methodology for diaphragm design. The site is Charleston (SC), SDC D, soil class F (Ss=1.39, S1=0.4).…”

Section: Pdh Structure Lfrs Designmentioning

confidence: 99%

Seismic Design Methodology Document for Precast Concrete Diaphragms

Fleischman¹

2014

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The design procedure in PART 1 is part of a new seismic design methodology for precast concrete diaphragms. The design methodology and procedure are the product of a large multi-university research project initiated and guided by the Precast/Prestressed Concrete Institute (PCI) and co-funded by PCI, the National Science Foundation (NSF) and the Charles Pankow Foundation (CPF), termed the Diaphragm Seismic Design Methodology (DSDM) project.

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“…A preprocessing stage to code compression is discussed in [16]. First, a program is partitioned into regions of high auto-correlation, which are then rescheduled such as to increase their prediction probability for a given compression engine.…”

Section: Compilation Schemesmentioning

confidence: 99%

Exploiting function similarity for code size reduction

et al. 2014

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For cost-sensitive or memory constrained embedded systems, code size is at least as important as performance. Consequently, compact code generation has become a major focus of attention within the compiler community. In this paper we develop a pragmatic, yet effective code size reduction technique, which exploits structural similarity of functions. It avoids code duplication through merging of similar functions and targeted insertion of control flow to resolve small differences. We have implemented our purely software based and platform-independent technique in the LLVM compiler framework and evaluated it against the SPEC CPU2006 benchmarks and three target platforms: INTEL X86, ARM based QUALCOMM KRAIT TM , and QUALCOMM HEXAGON TM DSP. We demonstrate that code size for SPEC CPU2006 can be reduced by more than 550KB on X86. This corresponds to an overall code size reduction of 4%, and up to 11.5% for individual programs. Overhead introduced by additional control flow is compensated for by better Icache performance of the compacted programs. We also show that identifying suitable candidates and subsequent merging of functions can be implemented efficiently.

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Code optimization for code compression

Cited by 5 publications

References 17 publications

Access pattern-based code compression for memory-constrained systems

Access pattern-based code compression for memory-constrained systems

Seismic Design Methodology Document for Precast Concrete Diaphragms

Exploiting function similarity for code size reduction

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